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Personalization Engineer Jobs (NOW HIRING)

Academy, Ltd.

Manager Personalization

Katy, TX · On-site

Partner with data science, UX, and engineering teams to implement real-time personalization using customer data, browsing behavior, and purchase history. * Own the push notification program ...

Posh

Senior Software Engineer, Personalization

New York, NY · On-site

$180K - $220K/yr

Lead the productionalization of personalization and classification algorithms. * Build with data ... Provide mentorship to engineers, fostering a culture of growth and collaboration. Ideal Candidate ...

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Personalization Engineer information

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$39K

$101.8K

$137.5K

How much do personalization engineer jobs pay per year?

As of Sep 14, 2026, the average yearly pay for personalization engineer in the United States is $101,752.00, according to ZipRecruiter salary data. Most workers in this role earn between $84,000.00 and $116,500.00 per year, depending on experience, location, and employer.

What is a personalization engineer?

A Personalization Engineer is a technology professional who designs, develops, and maintains systems that tailor digital experiences to individual users. They use data analysis, machine learning, and algorithms to create customized content, recommendations, or user interfaces on platforms like websites, apps, or e-commerce stores. Their goal is to improve user satisfaction and engagement by delivering relevant and personalized experiences based on user behavior and preferences.

How does a personalization engineer typically collaborate with data scientists and product teams?

Personalization Engineers work closely with data scientists to interpret user data and develop algorithms that tailor content or experiences to individual preferences. They also partner with product managers and designers to ensure that personalization features align with product goals and enhance user satisfaction. Regular cross-functional meetings and agile workflows are common, allowing engineers to quickly iterate on models and integrate feedback from various stakeholders. This collaborative environment helps ensure that personalization solutions are both technically sound and user-centric.

What are the key skills and qualifications needed to thrive as a personalization engineer, and why are they important?

To thrive as a Personalization Engineer, you need a strong background in computer science, data analysis, and machine learning, often supported by a relevant degree. Familiarity with tools and frameworks such as Python, TensorFlow, recommendation systems, and A/B testing platforms is typically required. Analytical thinking, creativity, and collaborative communication are crucial soft skills for designing personalized user experiences and working with cross-functional teams. These skills and qualities are essential for delivering impactful, data-driven personalization strategies that enhance user engagement and business outcomes.

What is the difference between Personalization Engineer vs Data Scientist?

AspectPersonalization EngineerData Scientist
Required CredentialsBachelor's in CS, Engineering, or related; experience in personalization algorithmsBachelor's or higher in CS, Statistics, or related; advanced analytics skills
Work EnvironmentDevelops and implements personalization features within tech teamsAnalyzes data to extract insights, often collaborating with product teams
Employer & Industry UsageTech companies, e-commerce, media platformsTech firms, finance, healthcare, research institutions

Personalization Engineers focus on building and optimizing algorithms for tailored user experiences, while Data Scientists analyze data to inform business decisions. Both roles require strong technical skills but differ in their primary focus and daily tasks.

What cities are hiring for Personalization Engineer jobs?

Cities with the most Personalization Engineer job openings:

What are popular job titles related to Personalization Engineer jobs?

For Personalization Engineer jobs, the most frequently searched job titles are:

Infographic showing various Personalization Engineer job openings in the United States as of September 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $101,752 per year, or $48.9 per hour.

Machine Learning Engineer - Search, Ranking & Personalization

New York, NY • On-site

Fuku
Food Services and Drinking Places • 51 - 200 employees
Learn more about Fukuexternal

$190K - $260K/yr

Full-time

Re-posted 9 days ago

Job description

*Machine Learning Engineer - Search, Ranking & Personalization*
*Stage:* Seed
*Founded:* 2022
*Key Job Information*
- *Location:* New York, NY / San Francisco, CA (Remote OK)
- *Employment Type:* Full-Time
- *Experience Level:* 3+ years
- *Salary Range:* $190,000 - $260,000 per year
- *Equity:* Competitive equity package
- *Visa Sponsorship:* H-1B, O-1, OPT
*About the Company*
Client is a fast-growing shopping platform with over 350,000 active users and a 90% retention rate. The company is focused on building intelligent, personalized search and ranking systems to help users discover and trust products at scale. The team is composed of experienced engineers from leading consumer tech companies such as Pinterest and Amazon.
*Role Summary*
As a Machine Learning Engineer at Client's company, you will join the ML team to design, build, and scale machine learning systems that drive search, ranking, and personalization across a platform serving hundreds of millions of items daily. This is a highly impactful role where your work directly influences user retention and trust. You will collaborate with a world-class team of engineers and play a key part in defining the ML search and personalization strategy from the ground up. The position is open to fully remote candidates.
*Key Responsibilities*
- Design, train, and deploy large-scale search, ranking, and personalization models.
- Handle hundreds of millions of items daily with high performance and reliability.
- Collaborate closely with backend and infrastructure teams to integrate ML models into production (GraphQL, Prisma, Node.js, Python, gRPC/Protobuf).
- Continuously improve model accuracy and system scalability.
- Contribute to product direction and technical roadmap for Client's ML systems.
*Requirements*
*Must-Have Qualifications:*
- Minimum of 3+ years professional experience building and deploying ML models in production.
- Proven experience with ranking, recommendation, or personalization systems.
- Proficiency in PyTorch and large-scale data processing for real-time inference.
- Strong backend integration experience (GraphQL, Prisma, Node.js, Python, gRPC/Protobuf).
- Willingness to work in a high-intensity, fast-paced startup environment.
- Based in New York or remote in San Francisco.
*Preferred Background:*
- Current or prior experience at companies like DoorDash, Etsy, Pinterest, Amazon, or eBay.
- Previous work on consumer-facing search or recommendation products.
*Benefits & Perks*
- $190K-$260K base salary plus competitive equity.
- Direct impact on a core product with a massive, high-retention user base.
- Work alongside top-tier engineers from leading consumer tech companies.
- Fast-paced startup culture with rapid iteration and experimentation.
- Opportunity to build the ML search and personalization strategy from scratch.
*Interview Process*
1. Intro call with Head of Recruiting
2. Technical Interview
3. Coding Interview
4. CTO Interview
5. Onsite Interview
6. Offer Extended
7. Hire
*Candidate Guidelines*
*Green Flags:*
- Experience solving large-scale consumer search/ranking challenges (e.g., Pinterest, Meta, TikTok, Amazon Ads).
- Strong track record shipping high-impact ML features in consumer products.
- Early-stage or startup experience with end-to-end ownership of ML pipelines.
- Demonstrated "builder" mindset - side projects, prototypes, hackathon wins.
- High intrinsic motivation and interest in future entrepreneurship.
*Red Flags:*
- Primarily B2B search experience with limited data complexity.
- Research-only background without production deployment.
- Prefers management over hands-on technical work.
- Struggles with ambiguity or high-intensity work environments.
- Unwilling to relocate or adapt to NYC-based team culture.
*Ideal Companies*
- Amazon
- eBay
- Pinterest
- DoorDash
- Etsy
Fuku logo

About Fuku

Sourced by ZipRecruiter

Industry

Food services and drinking places

Company size

51 - 200 Employees

Headquarters location

New York, NY, US

Year founded

2015

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